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相关论文: A Survey on Image-text Multimodal Models

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Multimodal Large Language Models (MLLMs) combine the natural language understanding and generation capabilities of LLMs with perception skills in modalities such as image and audio, representing a key advancement in contemporary AI. This…

Large Language Models (LLMs), AI-driven models that can achieve general-purpose language understanding and generation, have emerged as a transformative force, revolutionizing fields well beyond Natural Language Processing (NLP) and…

信息论 · 计算机科学 2024-02-27 Ali Maatouk , Nicola Piovesan , Fadhel Ayed , Antonio De Domenico , Merouane Debbah

The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language processing and moving towards multi-modal functionality.…

Mental health is increasingly critical in contemporary healthcare, with psychotherapy demanding dynamic, context-sensitive interactions that traditional NLP methods struggle to capture. Large Language Models (LLMs) offer significant…

计算与语言 · 计算机科学 2025-06-30 Hongbin Na , Yining Hua , Zimu Wang , Tao Shen , Beibei Yu , Lilin Wang , Wei Wang , John Torous , Ling Chen

In recent years, multi-modal machine translation has attracted significant interest in both academia and industry due to its superior performance. It takes both textual and visual modalities as inputs, leveraging visual context to tackle…

计算与语言 · 计算机科学 2024-05-24 Huangjun Shen , Liangying Shao , Wenbo Li , Zhibin Lan , Zhanyu Liu , Jinsong Su

Large language models (LLMs) have emerged as powerful tools with transformative potential across numerous domains, including healthcare and medicine. In the medical domain, LLMs hold promise for tasks ranging from clinical decision support…

计算与语言 · 计算机科学 2024-05-14 Xiaolan Chen , Jiayang Xiang , Shanfu Lu , Yexin Liu , Mingguang He , Danli Shi

Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and…

计算机视觉与模式识别 · 计算机科学 2023-10-20 Zhaoyi Sun , Mingquan Lin , Qingqing Zhu , Qianqian Xie , Fei Wang , Zhiyong Lu , Yifan Peng

Text embedding has become a foundational technology in natural language processing (NLP) during the deep learning era, driving advancements across a wide array of downstream tasks. While many natural language understanding challenges can…

计算与语言 · 计算机科学 2025-10-22 Zhijie Nie , Zhangchi Feng , Mingxin Li , Cunwang Zhang , Yanzhao Zhang , Dingkun Long , Richong Zhang

Instruction-tuned large language models (LLMs) have demonstrated promising zero-shot generalization capabilities across various downstream tasks. Recent research has introduced multimodal capabilities to LLMs by integrating independently…

计算与语言 · 计算机科学 2023-11-29 Utsav Garg , Erhan Bas

In many scientific fields, large language models (LLMs) have revolutionized the way text and other modalities of data (e.g., molecules and proteins) are handled, achieving superior performance in various applications and augmenting the…

计算与语言 · 计算机科学 2024-10-01 Yu Zhang , Xiusi Chen , Bowen Jin , Sheng Wang , Shuiwang Ji , Wei Wang , Jiawei Han

Attracted by the impressive power of Multimodal Large Language Models (MLLMs), the public is increasingly utilizing them to improve the efficiency of daily work. Nonetheless, the vulnerabilities of MLLMs to unsafe instructions bring huge…

计算机视觉与模式识别 · 计算机科学 2024-06-21 Xin Liu , Yichen Zhu , Yunshi Lan , Chao Yang , Yu Qiao

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

计算与语言 · 计算机科学 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

In recent years, large language models (LLMs) have driven major advances in language understanding, marking a significant step toward artificial general intelligence (AGI). With increasing demands for higher-level semantics and cross-modal…

计算与语言 · 计算机科学 2025-09-30 Yuntao Shou , Tao Meng , Wei Ai , Keqin Li

This paper explores the advancements and applications of large-scale models in the medical field, with a particular focus on Medical Large Models (MedLMs). These models, encompassing Large Language Models (LLMs), Vision Models, 3D Large…

人工智能 · 计算机科学 2025-10-08 YunHe Su , Zhengyang Lu , Junhui Liu , Ke Pang , Haoran Dai , Sa Liu , Yuxin Jia , Lujia Ge , Jing-min Yang

Recent advancements in Large Language Models (LLMs), particularly those built on Transformer architectures, have significantly broadened the scope of natural language processing (NLP) applications, transcending their initial use in chatbot…

计算与语言 · 计算机科学 2024-05-29 Chen Wang , Jin Zhao , Jiaqi Gong

Large language models (LLMs) have rapidly evolved from general-purpose systems to multimodal models capable of processing text, images, and audio. As both general-purpose LLMs (GLLMs) and multimodal LLMs (MLLMs) gain widespread adoption,…

软件工程 · 计算机科学 2026-04-08 Yujian Liu , Xiao Yu , Jacky Keung , Xing Hu , Xin Xia , Xiaoxue Ma

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and…

The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability to perform systematic, transparent, and verifiable reasoning, a cornerstone of clinical practice.…

计算与语言 · 计算机科学 2025-08-04 Wenxuan Wang , Zizhan Ma , Meidan Ding , Shiyi Zheng , Shengyuan Liu , Jie Liu , Jiaming Ji , Wenting Chen , Xiang Li , Linlin Shen , Yixuan Yuan